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Why Data Science Must Inherently be Interdisciplinary
Dec 1, 2020
01:00 PM - 02:00 PM (America/New_York)

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Join us for a special session with former Dean and Professor Xiao-Li Meng as he discusses the importance of a broader vision around our relationship with data and "data science":

1) Why is a multidisciplinary approach to data, its collection, analysis and application important?  

2) The challenges of privacy, data collection and analysis. Covid-19, individualized medicine and beyond 

3) Data and AI: The dangers inherent in data automation

4) Data science for all: Philosophical and ethical challenges, the Oscars, US census and a crunchy okra recipe: the Harvard Data Science Review and the interconnectedness of thought


About Professor Xiao-Li Meng

Xiao-Li Meng, Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review, Meng was named the best statistician under the age of 40 by COPSS (Committee of Presidents of Statistical Societies) in 2001, and he is the recipient of numerous awards and honors for his more than 150 publications. In 2020, he was elected to the American Academy of Arts and Sciences. Meng received his BS in mathematics from Fudan University in 1982 and his PhD in statistics from Harvard in 1990. He was on the faculty of the University of Chicago before returning to Harvard, where he served as the Chair of the Department of Statistics (2004-2012) and the Dean of Graduate School of Arts and Sciences (2012-2017).


Membership is $49 a year. To join, go to www.Harvardae.org/join

Please note that registration for this event closes 1 hour prior to the start of the session.

Organiser : Harvard Alumni Entrepreneurs (HAE)

Harvard Alumni Entrepreneurs (HAE)

For more information, email info@Harvardae.org

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Why Data Science Must Inherently be Interdisciplinary

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